News from the Collective

Just a few days ago,  London Metro Police Officer Wayne Couzens pled guilty to the rape and murder of Sarah Everard by, a 33-year-old woman he abducted while she walked home from a friend’s house.  Since the news broke of her disappearance in March 2021, the UK has been going through a moment of national “soul-searching.” The national reckoning has included a range of discussions–about casual and spectacular misogynistic violence, about a victim-blaming criminal justice system that fails to address said violence–and responses, including a vigil in south London that was met with aggressive policing, that has itself entered into and furthered the UK’s soul-searching. There has also been a surge in the installation of personal safety apps on mobile phones; One Scream (OS), “voice activated personal safety,” is one of them.

Available for Android and iOS devices, OS claims to detect and be triggered by a woman’s (true) “panic scream,” and, after 20 seconds and unless the alarm is cancelled, it will send both a text message to the user’s chosen contacts and an automated call with the location to a nominated contact. The app is meant to help women in situations where dialing 999, (assumed to be the natural and preferred response to danger), is not viable for the user and, in the ideal embodiment, this nominated contact, “the helper,” is the police. OS did automatically contact police (and required a paid subscription) in 2016, but it did not work out well and by 2018, was declared a work in progress: “What we really want is for the app to dial 999 when it detects a panic scream, but first, we need to prove how accurate it is. That’s where you come in. . .” OS is currently in beta and free (while in beta). It is unclear whether the developers have given up with that utmost expression of OS. 

OS is based on the premise that men fight and women scream —“It is an innate response for females in danger to scream for help”—and its correct functioning requires its users to be ready to do so, even if such an innate and instinctive response doesn’t come naturally to them: “If you do not scream, the app will not be able to detect you.” However, there are two discriminations in terms of scream analysis, in how the app discriminates while listening for and to screams, and in failing to detect or respond to them. The first has to do with who can use the app (i.e., whose panicked screams are able to trigger it) in the first place. This is presented in terms of gender and age—for the moment, OS can listen to “girls aged 14+ and women under 60,” where cisgender, as in anything OS, is taken for granted.   It is, however, a matter of acoustic parameters set by the developers (notably, of reaching a certain high pitch and loudness threshold). Which is why the app was implemented to include a “screamometer” for potential users to scream, hard, figure out, and see whether they can reach “the intensity that is needed to set it off” (confetti means they do). The second one discriminates true panicked screams from other types of screams (e.g., happiness, untrue panic). As presented by the developers, both discriminations are problematic and misleading, and so is “the science behind screaming” One Scream‘s website boasts of. 

The app does not quite distinguish true from fake screams, nor joy from panic for that matter.  Instead, One Scream listens for “roughness,” which a team of scream researchers—it truly is a “tiny science lesson” —has identified as scream’s “privileged acoustic niche” for communicating alarm.  According to this 2015 study in Current Biology,  “roughness” is the distinctive quality of effective, compelling human screams (and of artificial alarms) in terms of their ability to trigger listeners and in terms of perceived urgency. Abrupt increases in loudness and pitch are not unique to screams. The rougher the scream, then, the greater its perceived “alarmess” and its alarming effect. That’s why developers say OS “hears real distress,” essentially “just as your own ear.” However, other studies suggest your own ears might not be so great at distinguishing happiness from fear and scream research, and particularly the specific “bit” OS builds on, by and large assumes, relies on, and furthers the irrelevance of “real” on the scream vocalizer end.  

In OS’s pledge to its users, the app’s fine-tuning to its scream niche—i.e., to rough temporal modulations between 30 and 150Hz—is as important, as is the developers (flawed) insistence on the irredeemably uniqueness of true panic’s scream vocalizations, which they posit are instinctive and can’t be plotted or counterfeit: “Experience has shown that it is difficult for women to fake their scream.” Yet, current scream analysis and research primarily and largely relies on screams delivered by human research subjects (often university students, ideally drama students) in response to prompts for the purposes of studying them as well as, especially, on screams extracted from commercial movies and sound effect libraries. The same applies to the other types of vocalizations (e.g., neutral and valenced speech, screamed sentences, laughter, etc.) produced or retrieved for the purposes of figuring out what it is that makes a scream a scream, and how to translate that into a set of quantifiable parameters to capitalize on that knowledge, regardless of the agenda. 

Because of their interest for audio surveillance applications, screams are currently a contested object and a hot commodity. Much as is the case with other scream distinction/detection enterprises, the initial training of OS most likely involved that vast and available bank of crafted scream renditions—by professional actors, machines, combinations of those, by and for an industry otherwise partial to female non-speech sounds—conveniently the exact type of “thick with body” female voicings OS is also invested in. For some readers, myself included, this might come across as creepy and, science-wise, flimsy. 

Scream research often relies on how human listeners recruited for the cause respond to audio samples. Apparently, whether the scream is “real,” acted, or post-produced is neither something study subjects necessarily distinguish nor a determining factor in how they rate and react. In terms of machines learning to scream-mine audio data, it is what it is: “natural corpora with extreme emotional manifestation and atypical sounds events for surveillance applications” are scarce, unreliable, and largely unavailable because of their private character. That is no longer the case for OS, which has been accruing, and machine-learning from, its beta-user screams as well as how users themselves monitor/rate their screams and the app’s sensibility. OS users’ screams might not be exactly ad lib, as users/vocalizers first practice with the “screamometer” to learn to scream for and as a means to interface with OS, but it’s as natural a corpora as it gets, and it’s free for the users of the screams. OS not only echoes “voice stress analysis” technologies invested in distinguishing true from fake or in ranking urgency, but, as part and parcel of a larger scream surveillance enterprise, also public surveillance technologies such as ShotSpotter, all of which Lawrence Abu Hamdan has brilliantly dissected in his essay on the recording of the police gunshots that killed Michael Brown in Ferguson, Missouri in 2014.

Chilla is a strikingly similar app developed and available in India—although there’s a nuanced difference in the developer’s rationale for Chilla, which in its pursuance of scream-activated personal safety also aims to compensate for the fact that many girls and women don’t call “parents or police” for help when harassed or in danger. As presented, Chilla responds both to assaults and to women’s ambivalence towards their guardians. The latter is, too, a manifestation of the breadth of gender-based violence as a socio-cultural problem, one that Chilla is trained to fail to listen to and one that, because of OS’s particular niche user market, is simply out of the purview of its UK counterpart.

That problem–and that failure–is neither exclusive to India nor to scream-activated personal safety apps. Calling 999 in the UK, 911 in the US, or 091 in Spain, where I am writing, doesn’t come naturally to many targets of sexual and gender-based violence because they don’t conceive police as a help or because, directly, they see it as a risk—to themselves and/or to others. As Angela Ritchie has copiously documented in Invisible No More: Police Violence Against Black Women and Women of Color, women of color and Black women in particular are at extremely high risk for rape and sexual abuse by police officers, as high as 1 in 5 women in New York City alone.

OS, then,  is framed as a pragmatic, partial answer to a problem it doesn’t solve: “We should never have to dress in a certain way…but we do.” The specifics of how OS would actually “save” or even has saved its users in particular scenarios go unexplained, because OS is meant to help with feeling safe; getting into the details, and the what ifs, compromises that service. This sense of safety has two components and is based on two promises: one, that OS will listen to your (panic) scream, and, two, as of now via the intermediacy of your contacts, the police will go save you. The second component and its assumed self-evidence speaks to the app’s whiteness and of its target market of white, securitized, cisgender female subjects. 

Over and above its acoustic profiling, the app is simply not designed with every woman in mind. OS’s branding is about a certain lifestyle—of going for early runs and dates with cis-men, of taking time for yourself because you’re super busy at your white-collar job and going for night runs, of taking inspiration from “world” women and skipping if running isn’t for you.  This lifestyle is also sold: sold as always under the threat of rape–despite its “rightfulness”–sold in a way that animates the feelings of insecurity and disempowerment that One Scream advertizes itself as capable of reversing.  Safety, then, is sold as retrievable with OS. 

Wearable or otherwise portable technologies to keep women “safe,” specifically from sexual assaults, are not new and are varied. These have been vigorously protested, particularly from feminist standpoints other than the white, securitized, capitalist brand OS professes—because, in (partly) delegating safety on technologies women then become personally responsible for, these technologies  further “blame” women.  For authorities and the patriarchy, this shift in blame is a relief. In discussing the racialized securitization of US university campuses, Kwame Holmes notes how despite “reactionary attacks” on campus feminism (e.g., so-called “snowflakes” complaining about bad sex) and authorities’ effective reluctance to acknowledge and challenge rape culture, anti-sexual assault technologies tend to be welcomed and accepted. As Holmes also notes, there’s no paradox in that. Those technologies flatten the discussion, deactivate more radical feminist critiques and potential strategies, and protect the status quo—not so much women and not those who, whenever an alarm sounds and especially when security forces respond, readily become insecure.  

It is not a stretch to think that OS could potentially amplify the insecurities of Black and brown people subject to white panic (screams) and to its violence, something other audio surveillance technologies are already contributing to, at least it’s not a greater stretch than to entertain situations in which police would show up and save an OS user before it’s too late. Even if it’s never triggered, as developers seem to assume will be the case for the majority of installed units—”Many people have never faced a situation where they have had to panic scream”—it’s trapped in a securitization logic that ultimately relies on masculine authority, one that calls for the expansion of CCTV cameras, wherein women are never quite secure (see Sarah Everard’s vigil). 

One Scream’s FAQs cover selected worries that users have or OS anticipates they might have. Among these, there are privacy concerns (i.e., does it listen to your conversations?) and the fear the alarm will activate “when it shouldn’t.” In the Apple Store user reviews, there’s a more popular type of concern: OS not responding to users’ screams. In other words, there’s simultaneously a worry about OS listening and detecting too much and about OS failing to listen “when it matters.” These anxieties around OS’s listening excesses and insufficiencies touch on (audio) surveillance paradoxical workings: does OS encroach on the everyday life of those within users’ cell phones’ earshot while not necessarily delivering on an otherwise modest promise of safety in highly specific scenarios? There’s a unified developer response to these concerns: OS “is trained to detect panic screams only.”

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Featured Image: By Flicker User Dirk Haun. Image appears to be a woman screaming on a street corner, but is actually an advertisement on the window of a T-Mobile cell phone shop (CC BY 2.0)

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María Edurne Zuazu works in music, sound, and media studies, and researches the intersections of material culture and sonic practices in relation to questions of cultural memory, social and environmental justice, and the production of knowledge (and of ignorance) in the West during the 20^th and 21^st centuries. María has presented on topics ranging from sound and multimedia art and obsolete musical instruments, to aircraft sound and popular music, and published articles on telenovela, weaponized uses of sound, music and historical memory, and music videos. She received her PhD in Music from The CUNY Graduate Center, and has been the recipient of Fulbright and Fundación La Caixa fellowships. She is a 2021-2022 Fellow at Cornell’s Society for the Humanities. 

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Flâneuse>La caminanta–Amanda Gutierrez

Sounding Out! Podcast #63: The Sonic Landscapes of Unwelcome: Women of Color, Sonic Harassment, and Public Space

Echo and the Chorus of Female Machines—AO Roberts

Vocal Gender and the Gendered Soundscape: At the Intersection of Gender Studies and Sound Studies–Christine Ehrick

Instagram’s Like Hiding Saga is a PR Stunt:

What Facebook’s Darling Hopes You’ll Forget About Social Media Metrics

By Ben Grosser

In the spring of 2019 Instagram announced to the world that it was going to test the hiding of visible “like” counts within its interface. In the words of Instagram Head Adam Mosseri, he hoped it would make the platform feel “much less pressurized” and less “like a competition.” This announcement came at a time when the social media companies were enduring significant scrutiny for their roles in the amplification and virality of disinformation, the erosion of democracy and civic debate, and the destruction of individual self-esteem that was so widely evident that the New York Times wrote: “that Instagram can feel ‘pressurized’ and trigger status anxiety is hard to dispute.”

So, when Instagram made its announcement that spring, not only did it make big headlines, but many publications took it as a given that the decision had been made: likes were going away. The tests to come were merely a formality, many presumed—most without asking what those tests might be testing for, or what different outcomes might mean for the future of visible like counts.

In other words, the media was duped. Despite their stories from the time heralding Instagram’s tests as evidence of the company’s newfound concern for user well-being, it was always inevitably going to lead to either no actual change, or, at best, an anemic one. This is because Instagram is a corporation whose profit depends on continued growth, fueled by the extraction of user data and the production of ever-rising platform engagement. Visible metrics have been, for its entire history, a key component of this production—I would argue they are the central mechanism responsible for Instagram’s success.

So, it should come as no surprise when, after two years of testing, Instagram’s Head reports that their “research” turned up no particular effects from hiding likes. One can hardly help but recall in response other moments from corporate history, such as when the tobacco companies said smoking wasn’t addictive, or when the energy sector says fracking isn’t bad for the environment. Apparently, if we’re to believe Instagram, it turns out that likes just don’t matter much. Nothing to see here!

My own research strongly contradicts Instagram’s findings. I originated the concept of social media “demetrication” in 2012 when I launched the artwork Facebook Demetricator, a free and open-source browser extension that hides all quantifications across the Facebook interface. In 2014 I published a peer-reviewed article about my findings. In 2017 I launched a Demetricator for Twitter, and in 2018 one for Instagram. After a decade of activity investigating, working to erase, and listening to users report about the effects of hiding likes (and other visible counts), it is abundantly clear that social media metrics have profound effects on users. When like/follower/share/etc. counts are hidden, users report feeling, for example, less anxious, less competitive, and less addicted to the platforms. They talk about feeling less compulsive in response to them, less manipulated by metrics to continually like, share, and post. And perhaps most importantly, when visible interface metrics are hidden, users learn and feel for themselves just how significantly their actions had been driven—almost automated—by the presence of the number.

Caption: The author’s original video from 2012 demonstrating and describing Facebook Demetricator, a browser extension that hides visible metrics across the Facebook interface

So what’s really happening with “like” counts? And why might Instagram’s findings be different from my own? Setting aside (for the moment) their vested interest in the perpetuation of platform metrics and their vague assertions without evidence or peer review, I would point to the company’s anemic implementation of metric erasure.

First, Instagram’s like hiding options are laborious to use. To hide others’ metrics takes 6 taps through menus to find the toggle for it, which is buried in “Privacy” settings. Burying that option behind so many steps discourages experimentation and individual testing, leaving the default option (showing likes) as the one most will stick with.

Second, hiding one’s own like counts is not only repeatedly laborious, but incomplete. If I want to hide my like counts on my own posts, I have to tap 3 more times to turn it on every time I post. I can’t just change that setting once and have it affect all posts in the future. More importantly, even when I turn off like counts for a specific post I’ve made, the interface continues to report that metric back to me in several ways. For example, it accumulates the counts into a red and white metric popup every time I load the app—and periodically thereafter (far left in the image below). Instagram also continues to show these counts whenever I look at my notifications tab (far right). In other words, one can’t really hide their own like counts.

Image: Visible like counts on my own posts after enabling Instagram’s option to hide them. On left, the counts as shown in the standard notifications popup that appears every time I load the app and periodically thereafter. In the middle is the count shown when I click “others” from the feed. On the right are the like counts as shown in the notifications tab.

Third is that Instagram has chosen to show all metrics by default. Interface defaults are powerful. They set the conditions upon which any adjustment is evaluated. And most users won’t ever change the defaults anyway. Mosseri reveals his hopes here when he suggests that even those who hide likes might “want to switch back” “after a couple weeks.”

Fourth is that Instagram leaves all other non-like metrics in place. So even if a user hides others’ like counts and (partially) hides their own, they’re still faced with an interface full of metrics. Comment counts, view counts, follower counts, notification metrics, etc. All of these influence the user, and will serve as a ready substitute for metric evaluation when navigating the feed (e.g., it’s easy enough to focus on comment counts if like counts are hidden).

In other words, Instagram’s like hiding test: 1) made it hard to toggle like count hiding on and off, 2) made it impossible to truly hide one’s own like counts, 3) split like metrics into different categories controlled from different parts of the interface, 4) set the default as showing like counts, and 5) left in place all other interface metrics. If a social media company wanted to create a user interface test designed to conclude that hiding like counts doesn’t change much, this would be it. And lo and behold, the outcome from their findings will be continued platform growth—at the continued expense of human anxiety, compulsion, addiction, and diminished well-being.

Ironically, Mosseri confirms some of these effects with his recent statements. For example, he said (as quoted by the BBC):

‘“The spirit of this is to give people a choice,” using the example of going through a break-up in a relationship or switching schools.’

So, Instagram found no particular effect on user well-being, but Mosseri uses moments of extreme life stress as the example for why one might want to hide likes?

Another example Mosseri gave was:

“Maybe you want to be a little bit less worried about how many likes everyone’s getting for a couple weeks or a couple of months, and then maybe you want to switch back.”

So, if you want less worry, you turn off likes? Sounds as if like counts do in fact affect user well-being.

I appreciate Instagram’s decision to enable the hiding of others’ likes. This change will help users blunt the competitive feelings those metrics produce. But the anemic half-implementation of hiding one’s own likes reveals they don’t really want the idea to catch on. Instagram has spent more than a decade conditioning users to focus on the numbers. Any transition away from metrics was thus going to require substantial rethinking of what the platform is and how it works. Tests and experiments would need care and rigor; instead, Instagram came back with small clunky tweaks. A real test would make possible complete erasure of all visible metrics: no like, comment, view, or follower counts anywhere in the interface. This would be accompanied by a one-tap toggle so that users already dependent on the numbers could feel comfortable experimenting with hiding/showing the metrics at any time.

In a statement, Instagram said they consulted with experts during the testing period. Experts in what?, I would ask. Though I’ve worked on this topic for ten years—and released Instagram Demetricator a year before Mosseri started talking about their idea of hiding likes—Instagram never reached out to me for any discussion. Yet, tellingly, I did hear from the company during this period when their legal arm acted to force Instagram Demetricator off the Chrome web store in 2020. Unsurprisingly, this mirrors the actions of their parent company, Facebook, who did the same thing against Facebook Demetricator in 2016. Thankfully, the Electronic Frontier Foundation worked pro bono on my behalf to get the Facebook version reinstated. Given the company’s now repeated attempts to knock my Demetricators off the web, I haven’t worked too hard to reverse this latest move.

This whole saga is a public relations stunt. Instagram announced to the world in 2019 that they were testing the hiding of likes. They gained tremendous positive press from this move, with many lauding how much Instagram cares about user well-being. They then proceeded not to hide likes for everyone but instead to test the feature for two years—an eternity given their resources and capacity—only to come back later and proclaim that hiding likes doesn’t matter much? Not only does this assertion contradict my own research and the experience of countless users, but Instagram has a vested interest in this finding.

Visible metrics are key to the production of user engagement. Engagement is essential for user growth and profit generation. Their hiding tests were incomplete, leaving a user’s own like counts visible in multiple places. They didn’t reach out to some (all?) of us with a long research history on the topic. And along the way they acted to block users from fully hiding metrics via my projects, and even added new metrics to their interface with the addition of Reels. I find their conclusions and statements difficult to trust and would encourage others to be skeptical as well. Always remember: Instagram is a Mark Zuckerberg property. When Mosseri says something, it should be treated with the same level of trust that Zuckerberg has earned.

As a coda, one final comment on timing. Why now? After two years of testing and all the positive press, why come back now and say they’re done? I would point to the strongly negative reaction to the recently floated idea of Instagram for Kids. Many of the concerns expressed thus far have centered on fears around what a platform like Instagram, with all of its negative effects on user well-being, would do to children. What better antidote than to come out in response and say hey, it turns out our research shows that like counts don’t have much effect on anyone, so don’t worry about it! When companies release PR disguised as research, the media should hold them accountable for it.

The mention of “air guitar” might conjure images of the Bill and Ted series. Or Risky Business. Or maybe even Joe Cocker at Woodstock. You might think of air guitar as an embarrassing fan gesture. So when you hear there’s an annual U.S. Air Guitar competition, you might imagine an entirely superficial practice without any artistic merit. Maybe you just think of it as gimmicky. Or a celebration of the worst aspects of classic rock fandom and the white male guitar heroes that often populate its pantheon. In all honesty, I thought all of these things at first, until I began to take the competition seriously. 

I did not realize, for example, that air guitar competitions have an enduring history since the late 1970s, existing as an incredibly influential popular music pantomime practice that informs platforms like TikTok. I did not realize how invested contemporary competitors could be—dedicating years to learning the craft. And I did not realize how these reconstructions of guitar solos could creatively rupture the relationship between guitar virtuosity and privileged identities in popular music’s past.

The U.S. Air Guitar Championships began in 2003 as the national branch of the Air Guitar World Championships, which began in 1996 in Oulu, Finland. The competition emerged as a bit of a joke alongside the Oulu Music Video Festival. Eventually, two people—Cedric Devitt and Kriston Rucker—founded U.S. Air Guitar, which expanded across the country (thanks, in part, to the influential documentary Air Guitar Nation). Today, folks compete in order to advance from local to regional to the national competition, ultimately hoping to be crowned the best air guitarist in the nation and sent to Finland to represent the United States (think: Eurovision but air guitar). United States air guitarists do incredibly well in the international competition, although they face formidable air guitarists from Japan, France, Canada, Australia, Russia, and Germany (as well as less-formidable air guitarists from elsewhere).

In each competition, competitors perform as personas, such as Rockness Monster, AIRistotle, Agnes Young, and Mom Jeans Jeanie. They don elaborate costumes. They painstakingly practice elaborate choreographies and compete in some of the most famous musical venues in the country—from Bowery Ballroom to the Black Cat. Competitors stage routines that bring a particular 60-second rock solo to life, using their bodies to simulate playing the real guitar (what air guitarists call “there guitar”). Think of these as gestural interpretations of the affective power of guitar solos, rather than a mechanical reproduction of particular chords, frets, and licks. They use their bodies to draw out timbre, rhythm, and pitch, and they also play with the juxtaposition of their own identities and those of the original artists. Judges evaluate performances based on three criteria:

· Technical merit (does the pantomime more or less correspond to the guitar playing in the music?)

· Stage presence (is it entertaining?)

· ‘Airness’ (does the performance transcend the imitation of the real guitar to become an art form in and of itself?)

Scores are given on a figure skating scale, from 4 to 6. So a perfect score is 666 from the three judges. Winners in the first round advance to the second round, where they must improvise an air guitar routine to a surprise song selection. 

As part of my ethnographic work on air guitar, I competed in a local competition, where I was crowned third best air guitarist in Boston in the year 2017 (a distinction that will likely never appear on my CV). I have also conducted fieldwork in Finland twice and attended countless competitions in the U.S. I judged the 2019 U.S. Air Guitar Championships in Nashville alongside Edward Snowden’s lawyer, which resulted in a three-way air off to crown a winner. 

Competitions depend on recruiting new competitors, celebrity judges, and large crowds, all of which can be at odds with creating an inclusive community. Organizers have worked hard to eliminate racist, sexist, ableist, and other forms of discriminatory language from judges’ comments. Women within U.S. air guitar have formed advocacy groups. The proceeds of the most recent competitions have been donated to Alabama Appleseed Center for Law and Justice, which took up the case of a disabled Black veteran named Sean Worsley who was incarcerated for playing air guitar to music at a gas station. Both organizing bodies at the national and international level emphasize world peace as central to their mission. 

Air guitar routines are themselves political statements too. These acts of musical interpretation enable women, BIPOC, and disabled performers to author sounds credited to guitar idols, like Eddie Van Halen or Slash. Performers make arguments about their access to popular music, using only their bodies. Sydney Hutchinson’s work  examines how air guitar can challenge Asian American stereotypes and gendered conceptions of dance. 

My current work revolves around disabled air guitarists. Andres SevogiAIR drew me in, as a result of his expressive flamenco-inspired seated style he called “chair guitar.” He passed away but left me with an enduring appreciation for air guitar’s ability to challenge conventional virtuosity, a term that can often reproduce an ableist link between physical ability and musical virtue. I came to appreciate how air guitarists could invent imaginary instruments that serve their particular bodies. I witnessed competitors coupling chronic illness and impairments with air guitar routines, as well as competitors using air guitar to fully amplify their struggles with cancer.

I also came to appreciate how air guitarists embrace stigma (e.g., madness, craziness, and gendered forms of listening), turning taboo into a source of creativity. This led to academic writing that traces the history of madness in relation to air guitar, showing how imaginary instrument playing has often been pathologized, and yet contemporary disabled air guitarists reclaim these accusations of insanity as a source of power. 

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A few weeks ago, I received a request from Lieutenant Facemelter to judge the Midwestern Online Regional U.S. Air Guitar Competition. I accepted. As with many things these days, the contemporary competition has morphed into a Twitch-hosted online spectacle, featuring combinations of live and pre-recorded elements. One woman gave birth between first- and second-round performances (made possible by a multi-day filming period for an asynchronous part of the online competition). One man’s air guitar performance evoked an exorcism in his basement. Another middle-aged competitor competed while suffering the side effects of his second shot of coronavirus vaccine, ultimately winning the competition with a pro-vaccination message. His parents appeared in the livestream when he accepted the award, and the host of the show–the Master of Airimonies–jokingly said to them: “You two must be so proud.” 

I think of U.S. Air Guitar as a stained-glass window, through which prisms of popular music history shine through. The competition can bring troubling facets of that history to light, but the competition can also revise that history (or, at least, reimagine how that history can influence the future). Either way, performers celebrate the idea that rock solos live most powerfully in the embodied listening practices of everyday people. Listening becomes the subject of these performances–the source material for these persuasive displays of music reception. Indeed, air guitar can be one of the strangest things you’ll never see. 

The competition continues this summer. 

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Featured Image: US Air Guitar National Finals, The Midland Theater, Kansas City, MO, August 9, 2014, by Flickr user Amber, (CC BY-NC-ND 2.0)

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Byrd McDaniel | Byrd is a scholar who researches disability, digital cultures, and popular music. He currently works as a Postdoctoral Fellow in the Fox Center for Humanistic Inquiry at Emory University. His forthcoming book–Spectacular Listening— traces the rise of contemporary practices that treat listening as a performance, including air guitar, podcasts, reaction videos, and lip syncing apps. Byrd is enthusiastic about work that addresses any facet of air guitar, including global and historical approaches. He welcomes outreach from those who want to research these topics.

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SO! Reads: Steph Ceraso’s Sounding Composition: Multimodal Pedagogies for Embodied Listening–Airek Beauchamp

Digital Analogies: Techniques of Sonic Play–Roger Moseley

Experiments in Aural Resistance: Nordic Role-Playing, Community, and Sound—Aaron Trammell

In de driedelige serie The Digitarian Society onderzoekt Tetem samen met mediakunstenaar Roos Groothuizen en gasten van het Institute of Network Cultures, Waag en PublicSpaces wat er nodig is om verder te komen in onze zoektocht naar een veiliger internet.

De bewustwording over internet dilemma’s in relatie tot online verslaving, privacy en verantwoordelijkheid groeit; niet alleen onder organisaties, in de media en bij de overheid, maar ook onder het ‘grote publiek’. We hebben allemaal wel eens gedacht om alternatieve apps, videoplatforms en social media te verkennen, maar we doen het niet massaal. Wat houdt ons tegen?

Deze serie events gaat verder in op de dilemma’s van de escape room tentoonstelling ‘I want to delete it all, but not now’ die Roos Groothuizen voor Tetem heeft ontwikkeld. Daarin komt de vraag naar voren wat ons tegenhoudt om te stoppen met diensten van bijvoorbeeld Facebook en Google. Hoe worden we een digitariër, iemand die geen producten of diensten gebruikt van bedrijven die hun geld verdienen met het verkopen van persoonlijke data? Of is het mogelijk die moeilijke stap te verzachten door een flexidigitariër te worden, waar je zoveel mogelijke bewuste keuzes probeert te maken, maar nog geen afscheid wilt of kunt nemen van bijvoorbeeld Whatsapp? Het idee is dat we met kleine stappen onszelf en andere mensen en organisaties aansporen om bewuster te worden ten aanzien van de apps die we gebruiken en samen de stap naar een veiliger internet zetten. De drie events vinden plaats op verschillende platforms waarmee we als flexidigitariërs gaan experimenteren.

The Digitarian Society #1
Dinsdag 25 mei waren Geert Lovink en Chloë Arkenbout te gast bij Tatem.

De titel van de tentoonstelling ‘I want to delete it all, but now now’ van Roos Groothuizen komt uit het boek ‘Sad by Design’ door Geert Lovink. Het boek biedt een kritische analyse van de groeiende controverses op sociale media zoals nepnieuws, giftige virale memes en online verslaving. Tegelijkertijd roept Geert Lovink op tot het omhelzen van de digitale intimiteit van sociale media, berichtenverkeer en selfies, in de hoop dat verveling de eerste fase is van het overwinnen van ‘platformnihilisme’. Om daarna de afbraak van – verslaving aan – sociale media in te zetten.

Tijdens The Digitarian Society #1 ontdekten we wie de mensen achter het Institute of Network Cultures zijn en wat er bij hen persoonlijk is veranderd na het publiceren van het boek ‘Sad by Design’. Roos ging met Geert Lovink in gesprek over de schaduwzijde van online platforms, menselijke verlangens die ons tegenhouden en hoe je als individu de theorie in praktijk kunt brengen. In een gesprek met Chloë Arkenbout werd er  ingezoomd op Chloë’s onderzoek naar de macht van memes, media ethiek, morele verantwoordelijkheid, (digitaal) activisme, call out culture en de manieren waarop zij als nieuwe generatie onderzoekers met social media omgaat. Ook werd er Doen, durven of je data gespeeld.

Kijk hier The Digitarian Society #1 terug

The Digitarian Society #1 from Tetem on Vimeo.